Search Results for "visual-mingw"

...Instead of manually testing combinations, the tool performs grid search experiments by iterating across different models, prompt variations, and parameter configurations, allowing users to quickly identify optimal setups for specific tasks. It provides a visual interface where experiment results can be inspected, compared, and refined, making it especially useful for prompt engineering and benchmarking workflows. The system integrates directly with local or remote Ollama servers, enabling seamless access to models already deployed in a user’s environment. It also includes experiment logging and A/B testing capabilities, which allow users to compare outputs side by side and track performance metrics such as latency or token usage.

...Integrates all major LLMs: OpenAI, Anthropic, Google, xAI, Ollama, and more. MCP protocol, web search, JS/Python code execution, data visualization. Custom agents, visual workflows, artifact generation. Custom agents, visual workflows, artifact generation. Realtime voice chat with full MCP tool integration.

...We propose you a complete dev-friendly platform that ships with all the tools you need to build, deploy and manage production-grade chatbots in record time. Built-in Natural Language Processing tasks such as intent recognition, spell checking, entity extraction, and slot tagging (and many others). A visual conversation studio to design multi-turn conversations and workflows. An emulator & a debugger to simulate conversations and debug your chatbot. Support for popular messaging channels like Slack, Telegram, MS Teams, Facebook Messenger, and an embeddable web chat. An SDK and code editor to extend the capabilities. Post-deployment tools like analytics dashboards, human handoff and more.

An open source developer tool for building chat bots, apps and custom integrations for major messaging platforms. Part of the Microsoft Bot Framework. We love bots, and want to make them easy and fun to build! Include Botkit into your Node application and boot up a controller that will define your bot's behaviors. In this case, we're setting up a bot to use with the Bot Framework Emulator. Tell the bot to listen for users saying "hello," and use `bot.reply` to send an immediate response....